Combining Deep Learning with Good Old-Fashioned Machine Learning
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Abstract (arXiv)
We present a comprehensive, stacking-based framework for combining deep learning with good old-fashioned machine learning, called Deep GOld. Our framework involves ensemble selection from 51 retrained pretrained deep networks as first-level models, and 10 machine-learning algorithms as second-level models. Enabled by today's state-of-the-art software tools and hardware platforms, Deep GOld delivers consistent improvement when tested on four image-classification datasets: Fashion MNIST, CIFAR10, CIFAR100, and Tiny ImageNet. Of 120 experiments, in all but 10 Deep GOld improved the original networks' performance.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 5 of its 29 references that are in the map. First posted on arXiv 8 Jul 2022.
Builds on
5 of 29 references.
References · 5
- 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
- 2016XGBoost: A Scalable Tree Boosting Systemcited by 5,120
- 2019Optuna: A Next-generation Hyperparameter Optimization Frameworkcited by 2,455
- 2021Tabular Data: Deep Learning is Not All You Needcited by 530
- 2022Neural Networks with A La Carte Selection of Activation Functionscited by 4
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Citing papers per year: 2023: 2.
2 papers.
- 2023Classy Ensemble: A Novel Ensemble Algorithm for Classificationcited by 1
- 2023A Melting Pot of Evolution and Learningcited by 0
- 2023A Melting Pot of Evolution and Learning8 Jun 2023
- 2023Classy Ensemble: A Novel Ensemble Algorithm for Classification21 Feb 2023